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<html><head><title>R: Likelihood Ratio Tests for Negative Binomial GLMs</title>
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<table width="100%" summary="page for anova.negbin {MASS}"><tr><td>anova.negbin {MASS}</td><td align="right">R Documentation</td></tr></table>
<h2>Likelihood Ratio Tests for Negative Binomial GLMs</h2>
<h3>Description</h3>
<p>
Method function to perform sequential likelihood ratio tests for Negative
Binomial generalized linear models.
</p>
<h3>Usage</h3>
<pre>
## S3 method for class 'negbin':
anova(object, ..., test = "Chisq")
</pre>
<h3>Arguments</h3>
<table summary="R argblock">
<tr valign="top"><td><code>object</code></td>
<td>
Fitted model object of class <code>"negbin"</code>, inheriting from
classes <code>"glm"</code> and <code>"lm"</code>, specifying a Negative Binomial
fitted GLM. Typically the output of <code><a href="glm.nb.html">glm.nb</a>()</code>.
</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
Zero or more additional fitted model objects of class <code>"negbin"</code>. They
should form a nested sequence of models, but need not be specified in any
particular order.
</td></tr>
<tr valign="top"><td><code>test</code></td>
<td>
Argument to match the <code>test</code> argument of <code><a href="../../stats/html/anova.glm.html">anova.glm</a></code>.
Ignored (with a warning if changed) if a sequence of two or more
Negative Binomial fitted model objects is specified, but possibly
used if only one object is specified.
</td></tr>
</table>
<h3>Details</h3>
<p>
This function is a method for the generic function
<code>anova()</code> for class <code>"negbin"</code>.
It can be invoked by calling <code>anova(x)</code> for an
object <code>x</code> of the appropriate class, or directly by
calling <code>anova.negbin(x)</code> regardless of the
class of the object.
</p>
<h3>Note</h3>
<p>
If only one fitted model object is specified, a sequential analysis of
deviance table is given for the fitted model. The <code>theta</code> parameter is kept
fixed. If more than one fitted model object is specified they must all be
of class <code>"negbin"</code> and likelihood ratio tests are done of each model within
the next. In this case <code>theta</code> is assumed to have been re-estimated for each
model.
</p>
<h3>References</h3>
<p>
Venables, W. N. and Ripley, B. D. (2002)
<EM>Modern Applied Statistics with S.</EM> Fourth edition. Springer.
</p>
<h3>See Also</h3>
<p>
<code><a href="glm.nb.html">glm.nb</a></code>, <code><a href="negative.binomial.html">negative.binomial</a></code>, <code><a href="summary.negbin.html">summary.negbin</a></code>
</p>
<h3>Examples</h3>
<pre>
m1 <- glm.nb(Days ~ Eth*Age*Lrn*Sex, quine, link = log)
m2 <- update(m1, . ~ . - Eth:Age:Lrn:Sex)
anova(m2, m1)
anova(m2)
</pre>
<hr><div align="center">[Package <em>MASS</em> version 7.2-44 <a href="00Index.html">Index]</a></div>
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